基于行为的移动协同感知模型研究

移动协同一般受到资源的限制和移动环境的干扰，影响协同工作的有效进行。基于行为（Activity）设计移动协同系统，以行为为中心构建系统，可以克服上述困难。其中，如何提供行为所围绕的感知信息是关键所在。文章提出了一个基于行为的移动协同感知模型，通过定义行动者实体、目标实体、行为阶段实体等一组感知实体对象及感知行为服务，来提供基于行为的感知信息，并在原型系统中进行了实现。模型提供了移动用户在协同工作行为中群组工作（Team Work）的所有感知要素，从而支持了用户有效完成协同工作。     

Pixel-wise Dense Detector for Image Inpainting

Recent GAN-based image inpainting approaches adopt an average strategy to discriminate the generated image and output a scalar, which inevitably lose the position information of visual artifacts. Moreover, the adversarial loss and reconstruction loss (e.g., ℓ₁ loss) are combined with tradeoff weights, which are also difficult to tune. In this paper, we propose a novel detection-based generative framework for image inpainting, which adopts the min-max strategy in an adversarial process. The generator follows an encoder-decoder architecture to fill the missing regions, and the detector using weakly supervised learning localizes the position of artifacts in a pixel-wise manner. Such position information makes the generator pay attention to artifacts and further enhance them. More importantly, we explicitly insert the output of the detector into the reconstruction loss with a weighting criterion, which balances the weight of the adversarial loss and reconstruction loss automatically rather than manual operation. Experiments on multiple public datasets show the superior performance of the proposed framework. The source code is available at https://github.com/Evergrow/GDN_Inpainting.     

面向比特币交易网络的拓扑结构可视探索方法

分析比特币交易网络有助于人们理解交易者在比特币交易中的交易模式.比特币交易网络的匿名性和其巨大的规模使得用户很难在分析前对整个交易网络产生大致的认知.提出了一种基于拓扑结构推荐的比特币交易网络可视分析方法.核心思想是为每个节点生成一个向量化表达,在用户交互的基础上,所提算法即可检测一系列相似的结构.案例分析证明了系统能够支持用户对比特币交易中的交易模式进行探索和分析.     

Fast and Error-Bounded Space-Variant Bilateral Filtering

The traditional space-invariant isotropic kernel utilized by a bilateral filter (BF) frequently leads to blurry edges and gradient reversal artifacts due to the existence of a large amount of outliers in the local averaging window. However, the efficient and accurate estimation of space-variant kernels which adapt to image structures, and the fast realization of the corresponding space-variant bilateral filtering are challenging problems. To address these problems, we present a space-variant BF (SVBF), and its linear time and error-bounded acceleration method. First, we accurately estimate spacevariant anisotropic kernels that vary with image structures in linear time through structure tensor and minimum spanning tree. Second, we perform SVBF in linear time using two error-bounded approximation methods, namely, low-rank tensor approximation via higher-order singular value decomposition and exponential sum approximation. Therefore, the proposed SVBF can efficiently achieve good edge-preserving results. We validate the advantages of the proposed filter in applications including: image denoising, image enhancement, and image focus editing. Experimental results demonstrate that our fast and error-bounded SVBF is superior to state-of-the-art methods.

     

Localized surface plasmon-induced emission enhancement of a green light-emitting diode

The output enhancement of a green InGaN/GaN quantum-well (QW) light-emitting diode (LED) through the coupling of a QW with localized surface plasmons (LSPs), which are generated on Ag nanostructures on the top of the device, is demonstrated. The suitable Ag nanostructures for generating LSPs of resonance energies around the LED wavelength are formed by controlling the Ag deposition thickness and the post-thermal-annealing condition. With a 20?mA current injected onto the LED, enhancements of up to 150% in electroluminescence peak intensity and of 120% in integrated intensity are observed. By comparing this with a similar result for a blue LED previously published, it is confirmed that surface plasmon coupling for emission enhancement can be more effective for an InGaN/GaN QW of lower crystal quality, which normally corresponds to the emission of a longer wavelength.     

Typoselectivity of Crude Geobacillus sp. T1 Lipase Fused with a Cellulose-Binding Domain and Its Use in the Synthesis of Structured Lipids

Typoselectivity of crude CBD-T1 lipase (Geobacillus sp. T1 lipase fused with a cellulose binding domain) was investigated. Multi-competitive reaction mixtures including a set of n-chain fatty acids (C8:0, C10:0, C12:0, C14:0, C18:1 n-9, C18:2 n-6 and C18:3 n-3) and tripalmitin-enriched triacylglycerols were studied in hexane. The crude CBD-T1 lipase discriminated strongly against C18:1 n-9 [competitive factor (α) = 0.23] and showed the highest preference for C8:0 (α = 1). Utilizing the catalytic properties of crude CBD-T1 lipase, acidolysis of soybean oil with C8:0 was selected as a model reaction to investigate the ability of the lipase to produce MLM-type (medium-long-medium) structured lipids. Several reaction parameters (added water amount, reaction temperature, substrate molar ratio and reaction time) examined for incorporating C8:0 into soybean oil, the optimum conditions were: 1:3 (soybean oil/C8:0) of molar ratio, 3 mL of hexane, 50 °C of temperature, 48 h of reaction time, 20 % of crude CBD-T1 lipase (w/w total substrates), and 7.5 % of water (w/w enzyme). Under these conditions, the incorporation of C8:0 was 29.6 mol%. The results suggest that crude CBD-T1 lipase, which showed different fatty acid specificity profiles, is a potential biocatalyst for the modification of fats and oils.     

铜电解阴极板主要参数的确定及其矫直过程模拟

针对设计的21辊矫直机,对其主要参数进行研究分析.在有限元理论分析的基础上,对整个矫直过程建立了符合实际工况的模型,运用ANSYS/LS-DYNA软件对铜电解阴极板的矫直进行模拟,利用LS-DYNA得到不同工艺参数矫直变形过程的仿真结果,基本上找到了模型各个参数对矫直效果的影响,并得到了铜电解阴极板合理的矫直参数.     

高体积分数的 SiCp/Al复合材料的 SPS致密化机理研究

运用放电等离子烧结（SPS）技术制备出体积分数达60％，致密度达99％的SiCp／Al复合材料．从烧结工艺的控制及电场的影响两方面对SPS烧结SiC，／Al复合材料的机理进行了研究，认为SPS烧结SiCp／Al复合材料的致密化过程主要依靠烧结温度、压力及升温速率的合理搭配，使Al熔融粘结SiC颗粒，而又不溢出模具；烧结过程中未发现明显的放电现象，可能由于电场太弱不足以引发放电．     

三向应力状态下混凝土强度和变形特性研究

对设计强度为１０MPa的混凝土立方体试件进行三轴压缩试验,系统研究了等围压条件下混凝土的强 度和变形特性,围压分别为０,４,８,１２,１６MPa５个量级;同时研究了不等围压条件下混凝土强度变化特性, 试验表明,随着围压增加,混凝土的极限抗压强度有明显增强的趋势;随着小主应力的增加,中主应力的影响 有减弱的趋势;峰值应力处应变随围压增加幅度显著。得出了在不同恒定围压下混凝土的应力应变全过程曲线; 通过与当前文献资料的对比分析,指出了在混凝土结构计算中适用的强度及变形表达式,为工程实践提供了 依据。     

SHS法工艺参数对制备氮化硅粉体的影响

本文采用自蔓燃高温合成方法(Self-propagating High-temperature Synthesis)简称(SHS)合成氮化硅粉体,借助于XRD、SEM等检测方法,分析了自蔓燃高温合成氮化硅过程中氮气、温度、稀释剂与孔隙率等方面的影响。结果表明:只要最高燃烧温度不高于相应氮气压力下Si3N4的热分解温度,就可以用SHS方法合成Si3N4;氮气压力下硅粉的自蔓燃合成反应,必须要引入Si3N4稀释剂,来控制反应温度,以获得高α相含量的粉体。压坯气孔率控制在30%~70%,否则反应不能进行。研究发现SHS法可以制备纯度较高的氮化硅粉体。此法较传统方法合成的氮化硅设备简单,成本低廉,纯度高,填充性及烧结活性好。